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A Contour Shape Description Method Via Transformation to Rotation and Scale Invariant Coordinates System

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Graphics Recognition. Ten Years Review and Future Perspectives (GREC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3926))

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Abstract

Rotation and scale variations complicate the matters of shape description and recognition because these variations change the location of points composing the shape. However, some geometric invariant points and the relations among them are not changed by these variations. Therefore, if points in image space depicted with the x-y coordinates system can be transformed into a new coordinates system that are invariant to rotation and scale, the problem of shape description and recognition becomes easier. This paper presents a shape description method via transformation from the image space into the invariant feature space having d- and c-axes: representing relative distance from a centroid and contour segment curvature (CSC) respectively. The relative distance describes how far a point departs from the centroid, and the CSC represents the degree of fluctuation in a contour segment. After transformation, mesh features were used to describe the shape mapped onto the d-c plane. Traditional mesh features extracted from the x-y plane are sensitive to rotation, whereas the mesh features from the d-c plane are robust to it. Experimental results show that the proposed method is robust to rotation and scale variations.

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References

  1. Zhang, D., Lu, G.: Review of shape representation and description techniques. Pattern Recognition 37, 1–19 (2004)

    Article  Google Scholar 

  2. Safar, M., Shahabi, C., Sun, X.: Image Retrieval by Shape: A Comparative Study. In: Proc. of the IEEE International Conference on Multimedia and Expo (I), pp. 141–154 (2000)

    Google Scholar 

  3. Loncaric, S.: A Survey of Shape Analysis Techniques. Pattern Recognition 31(8), 983–1001 (1998)

    Article  Google Scholar 

  4. Li Stan, Z.: Shape Matching Based on Invariants. In: Omidvar, O.M. (ed.) Progress in Neural networks: Shape Analysis, vol. 6, pp. 203–228 (1998)

    Google Scholar 

  5. Hu, M.K.: Visual Pattern Recognition by Moment Invariants. IRE Trans. on Information Theory 8, 179–187 (1962)

    MATH  Google Scholar 

  6. Keyes, L., Winstanley, A.: Using moment invariants for classifying shapes on large-scale maps. Computers, Environment and Urban Systems 25, 119–130 (2001)

    Article  Google Scholar 

  7. Tsirikolias, K., Mertzios, B.G.: Statistical Pattern Recognition using Efficient Two-Dimensional Moments with Applications to Character Recognition. Pattern Recognition 26(6), 877–882 (1993)

    Article  Google Scholar 

  8. Shen, D., IP Horace, H.S.: Discriminative wavelet shape descriptors for recognition of 2-D patterns. Pattern Recognition 32, 151–165 (1999)

    Article  Google Scholar 

  9. Chang, C.C., Hwang, S.M., Buehrer, D.J.: Shape Recognition Scheme Based on Relative Distances of Feature Points from the Centroid. Pattern Recognition 24(11), 1053–1063 (1991)

    Article  Google Scholar 

  10. Zhang, J., Zhang, X., Krim, H., Walter, G.G.: Object representation and recognition in shape spaces. Pattern Recognition 36, 1143–1154 (2003)

    Article  Google Scholar 

  11. Manay, S., Hong, B., Yezzi, A.J., Soatto, S.: Integral Invariant Signatures. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3024, pp. 87–99. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  12. Kliot, M., Rivlin, E.: Invariant-Based Shape Retrieval in Pictorial Databases. Computer Vision and Image Understanding 71(2), 182–197 (1998)

    Article  Google Scholar 

  13. Valveny, E., Dosch, P.: Symbol Recognition Contest: A Synthesis. In: Llados, J., Kwon, Y.B. (eds.) Graphics Recognition: Recent Advances and Perspectives, pp. 368–385 (2004)

    Google Scholar 

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© 2006 Springer-Verlag Berlin Heidelberg

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Kim, MK. (2006). A Contour Shape Description Method Via Transformation to Rotation and Scale Invariant Coordinates System. In: Liu, W., Lladós, J. (eds) Graphics Recognition. Ten Years Review and Future Perspectives. GREC 2005. Lecture Notes in Computer Science, vol 3926. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11767978_28

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  • DOI: https://doi.org/10.1007/11767978_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34711-8

  • Online ISBN: 978-3-540-34712-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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